Group 29 Presentation

Introduction

  • CD molecules are membrane proteins with diverse functions and distributions across immune cell types.

  • Their expression patterns help distinguish cell lineages and reveal functional relationships

Aim:

  • How do the expression of CD markers on lymphocyte subsets change during maturation?

  • How are fluorescence intensity, variability, and positivity (MedQb, CVQb, PEpos) related across CD markers in lymphocyte subsets?

DOI: 10.5772/intechopen.81568

Materials and Methods

  • Data from: Frontiers in Immunology, “B Cell Biology,” vol. 10, Oct. 23, 2019. doi: 10.3389/fimmu.2019.02434

  • Can be downloaded from their shiny app: http://bioinformin.cesnet.cz/CDmaps/

  • The data set contains:

    • 28340 observations of 8 variables

    • 114 unique CDs and 38 unique cell types

Sample of data_aug:

# A tibble: 5 × 8
  tissue CD        lineage     cell_type  hierarchy  CVQb  MedQb   PEpos
  <chr>  <chr>     <chr>       <chr>          <dbl> <dbl>  <dbl>   <dbl>
1 tonsil CD3_HIT3a B cells     CB                 3  57.1  707.   0.0782
2 tonsil CD32      B cells     CB                 3  87.4  939.   4.70  
3 blood  CD18      CD4 T cells TCD4TEMRA          4  86.8 3548.  85.5   
4 tonsil CD36      B cells     CD138posPC         4 567.  8466.   0.373 
5 blood  CD51      CD4 T cells TCD4CM             4 152.    56.2  1.78

Analysis 1

  • Skriv tekst her

Analysis 2

  • Wide variations in CD marker distribution

  • Tissue-related clusters are common

  • Some markers are universally expressed (e.g. CD45), with others are lineage-specific

Analysis 3

CVQb:

  • Blue lines show a negative correlation → higher CVQb = lower MedQb

  • Tonsil B cells: line is flat → almost no relationship

PEpos:

  • Pink lines show a positive correlation → higher PEpos = higher MedQb

Analysis 4

  • Table: B cells had the most significant markers, showing stronger activation changes.

  • B cells: Tonsil B cells are more activated (CD69, CD80), while blood B cells mature gradually (CD11a, CD80).

  • CD4 T cells: Mature from thymus to blood, losing CD10 and gaining CD25 and CD4_MEM-241.

  • CD8 T cells: Move from active thymus cells to mature blood cells with higher CD27 and CD95.

Analysis 5

  • CD4 and CD8 T cells go through parallel stages

  • How do the CD markers differ between CD4 and CD8 T cells for each stage?

    • As expected CD4 and CD8 are significant different for all pairs
    • CD59 is significant for all stages except TEMRA with a higher log(MedQb) for CD8
    • SP1am and Naive have the lowest number of significant CDs → CD4 and CD8 more similar in these stages

Discussion

Why did we choose the linear model to assess significant difference for CDs?

  • Simplicity

  • A two-way ANOVA could for example also have been used, but it depends on what the aim is.

Problems with missing values in the wide-format data set for PCA

  • Number of experiments for each CD differed → summarized the experiments by the mean

  • Not every CD marker was measured across all cell types → replaced the missing value with the median for that specific CD

  • Limits the variation in the data set, but necessary to avoid dropping observations